# Stereo Vision Based Vehicle Detection and Distance Estimation for Braking Anomaly Detection
> Rahmat M.A.

URL kanonis: https://discover.unhas.ac.id/publications/pub_scopus_105034908751
Jurnal / Konferensi: Proceedings 7th International Conference on Informatics Multimedia Cyber and Information System Icimcis 2025
Tahun terbit: 2025
DOI: https://doi.org/10.1109/ICIMCIS68501.2025.11327368
Citations: 0

## Authors
- Rahmat M.A.

## Abstract
Detecting sudden braking anomalies is crucial for enhancing traffic safety, particularly in dense urban environments such as Makassar, Indonesia. This study proposes a stereo camera based framework combined with preprocessing techniques to improve the accuracy of vehicle detection and distance estimation. A total of 3,270 stereo images were used to train and evaluate multiple YOLO models (YOLOv5 to YOLOv8) under two scenarios: one without preprocessing, and another with an enhanced preprocessing pipeline. Experiments were conducted over 100+ epochs using an NVIDIA Tesla T4 GPU. In Scenario 1, YOLOv5 achieved a mean average precision (mAP 50) of 92.90% and a mean absolute percentage error (MAPE) of 8.40%. In Scenario 2, after applying data augmentation, normalization, and contrast enhancement, the mAP 50 improved to 97.50% while the MAPE dropped significantly to 2.11%. These results demonstrate that integrating stereo vision with robust input enhancement can significantly boost object recognition and distance estimation, laying a solid foundation for effective detection of sudden braking events in complex traffic settings.

## Keywords
- Artificial intelligence
- Computer vision
- Preprocessor
- Computer science
- Anomaly detection
- Object detection
- Stereopsis
- Stereo cameras
- Mean absolute percentage error
- Stereo camera
- Pattern recognition (psychology)
- Data pre-processing
- Contrast (vision)
- Computer stereo vision
- Intelligent transportation system
- Stereo imaging
- Engineering
- Object (grammar)
- Mean squared error
- Image processing
- Distance measurement

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Sumber: Discover Unhas — RIMS Universitas Hasanuddin.
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